Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01bn9999183
Title: Default Probability and Information Asymmetry: An Analysis of Income-Contingent Loan Contracts
Authors: Ling, Daniel
Advisors: Morris, Stephen E.
Department: Economics
Class Year: 2016
Abstract: This thesis offers an analysis of default decisions in a market with considerable information asymmetry. We first develop a mechanism design framework to study the credit rationing problem in the market for income-contingent loans. Our em- pirical work follows the theoretical results by examining the determinants of default for student loan debtors. We add to the limited knowledge of student loan default by presenting a probit model of default probability for over two thousand borrowers of income-contingent student loans backed by the federal government. The exercise illustrates how borrower characteristics largely determine default probabilities across multiple specifications. We analyze the implications of this exercise by elucidating how borrower risk is perceived by government-sponsored agencies, which serve to as- sist creditors in originating income-contingent loans in an illiquid market. Looking at debt issues in the secondary loan market, we provide a decomposition of the origina- tion costs associated with raising capital and bringing the debt instruments to market. The results suggest that borrower risk is priced into the cost of debt issuance and government agencies are cognizant of repayment uncertainty. Upon reconciling the theoretical and empirical results, we provide commentary on the role of government intervention in providing liquidity for inefficient markets.
Extent: 82 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01bn9999183
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Economics, 1927-2016

Files in This Item:
File SizeFormat 
Economics_Senior_Thesis_Submission_Click_Here_To_Submit_dling_attempt_2016-04-13-14-50-28_ling_daniel.pdf506.29 kBAdobe PDF    Request a copy


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.